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Global vegetation gross primary production estimation using satellite-derived light-use efficiency and canopy conductance

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Yebra, Marta
Van Dijk, Albert
Leuning, Ray
Guerschman , Juan Pablo

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Elsevier

Abstract

Climate and physiological controls of vegetation gross primary production (GPP) vary in space and time. In many ecosystems, GPP is primary limited by absorbed photosynthetically-active radiation; in others by canopy conductance. These controls further vary in importance over daily to seasonal time scales. We propose a simple but effective conceptual model that estimates GPP as the lesser of a conductance-limited (F<inf>c</inf> ) and radiation-limited (Fr) assimilation rate. F<inf>c</inf> is estimated from canopy conductance while Fr is estimated using a light use efficiency model. Both can be related to vegetation properties observed by optical remote sensing. The model has only two fitting parameters: maximum light use efficiency, and the minimum achieved ratio of internal to external CO<inf>2</inf> concentration. The two parameters were estimated using data from 16 eddy covariance flux towers for six major biomes including both energy- and water-limited ecosystems. Evaluation of model estimates with flux tower-derived GPP compared favourably to that of more complex models, for fluxes averaged; per day (r2 =0.72, root mean square error, RMSE=2.48μmolCm2 s-1, relative percentage error, RPE=-11%), over 8-day periods (r2 =0.78 RMSE=2.09μmolCm2 s-1,RPE=-10%), over months (r2 =0.79, RMSE=1.93μmolCm2 s-1, RPE=-9%) and over years (r2 =0.54, RMSE=1.62μmolCm2 s-1, RPE=-9%). Using the model we estimated global GPP of 107PgCy-1 for 2000-2011. This value is within the range reported by other GPP models and the spatial and inter-annual patterns compared favourably. The main advantages of the proposed model are its simplicity, avoiding the use of uncertain biome- or land-cover class mapping, and inclusion of explicit coupling between GPP and plant transpiration.

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Remote Sensing of Environment

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2037-12-31
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